This invention relates to the general subject of the analysis and interpretation of the subsurface from seismic and seismic derived layer property data sets.
Seismic data is acquired to provide information about the subsurface structure, stratigraphy, lithology and fluids contained in the rocks. Acquired seismic data records are the response of a seismic energy source after passing through and being reflected by rocks in the subsurface. Seismic data can be acquired at or close to the earth""s surface or can be acquired along boreholes. After acquisition, seismic data is typically processed to a set of seismic traces, where each trace represents the seismic response at a certain surface x,y location. The trace itself consists of a series of samples of the seismic response, usually ordered to correspond to increasing seismic travel time or, after depth conversion, increasing depth. Dependent on the acquisition geometry, the seismic traces are usually processed and organized to form lines with regularly spaced traces along the surface. The seismic data along such lines can be viewed as sections through the earth. Seismic data is referred to as 2-D seismic data when the lines are in different directions or are far apart relative to the spacing of the traces. Seismic data is referred to as 3-D seismic data when the acquisition is such that the processing results in a set of seismic lines that are organized sequentially and where the x,y trace locations form a regular grid and such that the spacing of the seismic lines generally is within the same order of magnitude as the spacing of the traces within the lines. In practice, the lines along which the data is acquired are called inlines and lines orthogonal to the inlines are referred to as crosslines. FIG. 1 shows a seismic section taken from a 3-D seismic data cube. 2-D and 3-D seismic data sets are subsequently analyzed and interpreted, generally on computer workstations with specialized software, to reveal the subsurface structure, stratigraphy, lithology and fluids, and to so predict the location, structure, stratigraphy, lithology and fluid distribution of hydrocarbon reservoirs, associated aquifers and other subsurface features of interest.
The amplitude of seismic data changes with changing angle of incidence of the seismic waves reflecting from a rock boundary. These changes of amplitude with angle can hold valuable information about the types of rocks in the subsurface and fluids they contain. For this reason in modern seismic processing multiple seismic data sets for analysis and interpretation are routinely generated from acquired seismic data. Examples are seismic data sets obtained by stacking seismic traces over different ranges of acquisition offsets or ranges of angles of incidence of the seismic waves. Such data sets typically concern pressure wave data. Connolly (1999) discusses methods for generating such seismic data sets. FIG. 1 shown above is actually a section from a partial stack over near angles. FIG. 2 shows the corresponding far angle partial stack. Comparison clearly shows differences in the seismic amplitude behavior caused by the change in incidence angles. Besides pressure wave data, other types of seismic data may also be available. In so called multi-component data acquisition the volumes of pressure wave seismic data are further augmented with one or more volumes of shear wave or converted pressure to shear wave seismic data. This provides further information about the subsurface.
The amplitudes of pressure, shear and converted wave seismic data are primarily determined by the strength of the reflection of seismic waves at layer boundaries. The reflection strength in turn is determined by changes in certain physical parameters of the rocks when going from one layer to the next and the angle of incidence of the seismic waves at the layer boundaries. The physical rock parameters are determined by the physical properties of the rock matrix, i.e. the rock with empty rock pores, and fluids contained in the pores, jointly referred to as xe2x80x98rock property dataxe2x80x99. Changes in the rock matrix can be caused by changes in the lithology (rock mineral composition, porosity and build-up). Changes in fluids can arise from changes in the relative fractions of the fluid types: water, oil and gas and changes in the properties of the fluid types. Using modern computer algorithms, rock property data that is directly related to the amplitudes of the seismic data can be estimated from the seismic data. Such rock property data which is directly related to seismic data includes acoustic impedance, shear wave impedance, density, pressure wave and converted wave elastic impedance and functionally directly related parameters such as pressure and shear wave velocity or slowness, the Lame parameters and the Lame parameters multiplied by density. For the relationship of such parameters to seismic data see e.g. Castagna and Backus (1993). For the estimation of such rock properties from seismic data see e.g. Goodway et al. (1998), Connolly et al. (1999), Anderson and Bogaards (2000) and Pendrel et al. (2000). FIG. 3 shows an acoustic impedance section and FIG. 4 a shear impedance section which are derived from the seismic data shown in FIG. 1 and FIG. 2. The acoustic and shear impedance have been estimated using a seismic inversion method as described by Pendrel et al. (2000). Further rock property data can also be derived directly or indirectly using functional, statistical or other relationships between the different rock properties. For example geostatistics provides a powerful approach to derive further rock property parameters, see e.g. Torres-Verdin et al. (1999). Seismic derived rock property data can be directly used to analyze changes in lithology and fluids in layers. Also, information about structure and stratigraphy is maintained and often even enhanced relative to seismic data. Use of seismic derived rock property data in subsurface analysis and interpretation is therefore often preferred over the use of seismic reflection data. For the same reason the subject method is preferably applied to seismic derived rock property data.
Importantly, seismic derived rock property data directly characterize the properties of the earth""s layers, in contrast to seismic data that directly characterizes the reflection properties of layer interfaces. The fact that seismic derived rock properties characterize the properties of rock layers has as key advantage that they can be directly related to other measurements of the earth""s layer properties, such as obtained from well logs. For a further discussion of the benefits of carrying out subsurface analysis and interpretation in the layer domain, see e.g. Latimer et al. (2000).
Besides different seismic derived rock property data sets, further data sets, referred to as layer attribute data sets, may be also be available for analysis and interpretation. An example are the data sets derived from seismic derived rock property data sets where the amplitudes are a measure of the continuity (or discontinuity) of the layers. For example U.S. Pat. No. 5,838,634 describes a method that can also be applied to seismic derived rock property data. Yet further information may be available in the form of estimation uncertainties and other statistical measures about the various rock properties.
In summary, a wide range of seismic derived rock property, layer attribute and layer statistical data can be produced with methods among others from seismic data processing, estimation, inversion and (geo)statistics. As most of these data sets refer to the properties of layers, they are further referred to as xe2x80x98seismic derived layer propertiesxe2x80x99 to contrast them to seismic data and most common attributes directly derived from seismic data which characterize seismic reflections at layer interfaces.
Seismic derived layer properties can be interpreted with the same methods as available for seismic data. However, the seismic derived layer properties measure properties of a layer. This means that information about the layers and their properties is directly available and not indirectly through measurements of interface properties which are impacted by the properties of the layers above and below the interface. Further, seismic derived layer properties, as opposed to seismic reflection data, can be directly related to other measurements of those layer properties, for example as provided by well logs. These favorable features form the basis for a novel method for the analysis and highly automated interpretation of the subsurface from seismic derived layer property data.
The present invention provides a new and improved method for the joint analysis and interpretation of two or more seismic derived layer property data sets. The main steps in the method comprise respectively data input, data analysis, classification, spatial connectivity analysis and output of the results.
The input data for the process consists of seismic derived layer property data sets and data to define zones of interest within these data sets to which the classification and spatial connectivity analysis is applied. Further input is data that is used in an analysis step to define a layer parameter subspace or subspaces that are used to drive the classification process. This analysis data may consist of well log data, attribute horizons, the same data which is input for classification, other layer property data sets, statistical distribution functions or other any other data. The analysis input data must at least contain the same type of data as the classification input data.
After data input the next step is data analysis and subspace definition. In this step the analysis input data is analyzed, for example using crossplots, and one or more layer property parameter subspaces are defined, where the layer property parameters correspond to the parameters in the layer property data sets input to the classification.
The next step in the procedure is to classify the classification input data sets by scanning all points in these data sets falling within the zone of interest for points where the parameter values are such that they fall inside a selected subspace or subspaces.
The classification step is followed by a spatial connectivity analysis step. In this step points are selected based on their classification, and these points are analyzed to determine geobodies consisting of sets of spatially connected points.
After any of the above steps, results may be visually inspected. Based on these results input data and/or the parameters steering any of the above steps may be revised.
The main outputs of the process are data sets with the classification results and the geobodies. Further output may also be generated, for example in the form of maps capturing the geobodies.
The method is not limited to application in hydrocarbon exploration, development and production. The method may be applied to seismic data acquired for other subsurface analysis applications, for example for shallow gas detection, subsurface stability analysis, basin analysis, coal and other mineral resource exploration and mining, and water resource development. The method is equally suited for the analysis of echo-acoustic data acquired for medical and material investigations. dr
The file of this patent contains at least one drawing executed in color.
FIG. 1 is an example of a seismic reflection amplitude section from a 3-D seismic cube obtained from a partial stack over near angles of incidence. The seismic response is over a time gate encompassing a hydrocarbon reservoir sand. The display is in so called wiggle mode, where the black filled wiggles correspond to positive values in the traces of seismic data. Stronger reflections are indicated by larger excursions of the wiggles.
FIG. 2 shows the same section as in FIG. 1, but now from a partial stack over far angles of incidence. The arrows in FIG. 1 and FIG. 2 indicate areas with strong relative changes of seismic reflection amplitude with changing angle of incidence.
FIG. 3 shows a section of seismic derived rock property data, in this case acoustic impedance. The section is the same as in FIG. 1 and FIG. 2. Lighter colors correspond to higher impedance values.
FIG. 4 shows a second section of seismic derived rock property data, in this case shear impedance. The section is the same as in the previous figures. Lighter colors correspond to higher impedance values.
FIG. 5 is a flowchart showing the process steps in one embodiment of the new method.
FIG. 6 shows how a crossplot is used to define a subspace. A crossplot is shown of acoustic and shear impedance logs from a well close to the section shown in FIGS. 1-4. The crossplot points are classified into different lithologies using differently shapes symbols, where sands are coded as triangles. The crossplot points are further color coded with water saturation, such that light colors correspond to low water saturation (i.e. high hydrocarbon saturation). The polygon thus captures the subspace in the crossplot corresponding to hydrocarbon bearing sandstone.
FIG. 7 shows an example of classification results. The results are obtained by the application of the subspace defined by the polygon in FIG. 6 in the classification of the subsurface from acoustic and shear impedance 3D volumes, lines of which are illustrated in FIGS. 3and4. The 3D view shows all points in space which fall inside the subspace enclosed by the polygon, and thus have characteristics corresponding to those of hydrocarbon bearing sands.
FIG. 8 illustrates different possibilities for cell connectivity. From left to right are shown cell pairs where the cells are respectively face connected, edge connected and comer connected.
FIG. 9 shows the result of the connectivity analysis procedure applied to the classification results shown in FIG. 7. The three largest geobodies are shown. The results of the connectivity analysis show that hydrocarbons are located in multiple, spatially separate reservoir units.
FIG. 10 shows how a three-dimensional subspace is defined using multiple two-dimensional crossplots. In this case the three parameters are acoustic impedance, shear impedance and density. To define the three-dimensional subspace three two-dimensional crossplots are used, respectively for acoustic impedance and shear impedance, acoustic impedance and density, and shear impedance and density. As illustrated, a different polygon can be defined in each of the crossplots. The three two-dimensional polygons jointly define a three-dimensional subspace.
FIG. 11 shows the result of bringing in a third dimension to the example of FIGS. 6, 7 and 9 in the subspace definition, classification and connectivity analysis. In this case the additional dimension consists of a measure of geologic continuity. The third dimension is used to restrict the subspace defined in FIG. 6 to hold points with hydrocarbon bearing sands and with good continuity. As illustrated in FIG. 11, the classification and subsequent connectivity analysis show that two of the geobodies shown in FIG. 9 are each broken up into two separate geobodies.
FIG. 12 shows a map view of the depth in time to the top of the geobodies shown in FIG. 9. The color coding indicates depth in time, with the lighter colors corresponding to the shallower parts of the top of the geobodies.